Main window
Central work view with original image, automatically detected analysis image, histogram, and result tables.
Examples
Scientific Counter counts and measures objects in digital images: colonies, cells, particles, pores, holes in foams, and other clearly visible structures. This page summarizes typical workflow steps, settings, and result views.
Program windows and screenshots
The screenshots are integrated directly into the examples. They show individual windows and explain how each view is used in the analysis workflow.
Options
Color channel, filters, thresholds, object criteria, and output options are configured here.
Analysis parameters
Values such as size, brightness, shape factor, Feret diameter, convexity, or solidity can be selected for result display.
Analysis area
Relevant image regions can be restricted, for example for petri dishes, holders, or distracting image edges.
Object selection
Detected objects are checked by size, brightness, shape, and additional parameters, and filtered if needed.
Histogram
Distributions of object sizes or other parameters are shown graphically and support evaluation.
From image to result
The analysis follows a clear workflow: load an image, select color channel and analysis area, preprocess the image, detect objects, separate them if needed, and output results as a table, histogram, or report.
1. Load imageDigital images form the basis of automatic counting.
2. Prepare imageColor channel, inversion, filters, and thresholds improve detection.
3. Count objectsSize, brightness, and shape factor define the relevant objects.
4. Save resultCount, measurements, histogram, detailed data, and report are documented.
Analysis view with histogram
After analysis, the main window shows the original image, analysis image, size distribution, and key result values.
Histogram and measurements
The result view makes distributions visible and supports evaluation of object sizes and other parameters.
Typical applications
Count colonies
Automatic counting of bacterial colonies, for example on petri dishes or in standardized image series.
Analyze cells and particles
Detection of separate structures based on size, brightness, shape factor, and additional parameters.
Evaluate materials and pores
Evaluation of object count, density, porosity, and shape parameters for material-related questions.
Seeds / particles
Example for measuring individual objects with comparable shape.
Microstructures
Example for size determination of structures in an atomic force microscopy image.
Note: for reliable results, the relevant features should be clearly visible in the image and acquisition conditions should remain as constant as possible within a series.
Parameters explained visually
Analysis tasks differ in contrast, background, object size, and object shape. That is why the key image and object parameters can be adjusted precisely.
Select color channels
Depending on the image, a red, green, blue, or grayscale image may make the relevant objects more visible.
Reduce background and noise
Median and mean filters help with brightness gradients, image noise, and small disturbances.
Set threshold
The threshold determines which bright image regions are accepted as objects.
Define analysis area
Relevant image regions can be selected specifically, for example to exclude edges or holders.
Control, correction, and detail view
Review objects individually
Detected objects can be checked and evaluated based on size, brightness, and shape factor.
Optimize options
A test area allows quick evaluation of different settings before the entire image is analyzed.